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REFLECTANCE PRI DOES NOT EQUAL TRANSMITTANCE PRI

Starting from leaf reflectance and transmittance measurements, we calculated two substantially different values of the Photochemical Reflectance Index (PRI) for each of 22 corn leaves having leaf chlorophyll concentrations ranging from high to low. Leaf reflectance and transmittance were measured simultaneously, precluding changes in leaf light use efficiency (LEU) between measurements. We propose the proportion of leaves reflecting v. transmitting direct beam sunlight toward a canopy reflectance sensor is a potential source of variability in estimates of canopy bidirectional PRI.

Reflectance↗

Data from: Biomass yield, yield components and growing season phenotypic measurements of Miscanthus

For sustainable biomass production of Miscanthus × giganteus (hereafter miscanthus), understanding the impact of stand age and nitrogen (N) fertilization on biomass yield is crucial. This study investigated the effects of varying N fertilization rates (0, 56, 112, and 168 kg N ha-1) on yield components (tiller height, density, and weight) and their correlations with end-of-season biomass yield in miscanthus. We also explored end-of-season biomass yield prediction using in-season traits (canopy height, leaf area index (LAI), and leaf chlorophyll content (LCC)). The study was conducted at two sites in Illinois: a previously unfertilized 10-year-old miscanthus research stand at Urbana and a 16-year-old commercial stand at Pesotum with a history of annual 56N application. Results from 2018-2021 in Urbana and 2020-2021 in Pesotum showed increased biomass yields with N fertilization, varying by rate, year, and location. Biomass yield in Pesotum peaked at 56N, while in Urbana, it increased significantly at 112 kg N ha-1. Biomass yield was strongly correlated with tiller height and weight measured at Urbana across N rates. Morphological traits measured every 2-3 weeks during the 2020 and 2021 growing seasons showed that canopy height was the strongest single predictor of miscanthus biomass yield, followed by LCC. Mid-August to September measurements of these traits were the best predictors of biomass yield. Multiple regressions involving the canopy height and LCC further improved yield predictions. We conclude that while N enhances biomass yields of aging miscanthus, the optimum rate depends on the site, environmental conditions, and management.

Aging↗

Nitrogen fertilization effects on aged Miscanthus × giganteus stands: Exploring biomass yield, yield components, and biomass prediction using in–season morphological traits

For sustainable biomass production of Miscanthus × giganteus (hereafter miscanthus), understanding the impact of stand age and nitrogen (N) fertilization on biomass yield is crucial. This study investigated the effects of varying N fertilization rates (0, 56, 112, and 168 kg N ha –1 ) on yield components (tiller height, density, and weight) and their correlations with end-of-season biomass yield in miscanthus. We also explored end-of-season biomass yield prediction using in-season traits (canopy height, leaf area index, and leaf chlorophyll content [LCC]). The study was conducted at two sites in Illinois: a previously unfertilized 10-year-old miscanthus research stand at Urbana and a 16-year-old commercial stand at Pesotum with a history of annual 56N application. Results from 2018 to 2021 in Urbana and 2020 to 2021 in Pesotum showed increased biomass yields with N fertilization, varying by rate, year, and location. Biomass yield in Pesotum peaked at 56N, while in Urbana, it increased significantly at 112 kg N ha –1 . Biomass yield was strongly correlated with tiller height and weight measured at Urbana across N rates. Morphological traits measured every 2–3 weeks during the 2020 and 2021 growing seasons showed that canopy height was the strongest single predictor of miscanthus biomass yield, followed by LCC. Mid-August to September measurements of these traits were the best predictors of biomass yield. Multiple regressions involving the canopy height and LCC further improved yield predictions. We conclude that while N enhances biomass yields of aging miscanthus, the optimum rate depends on the site, environmental conditions, and management history.

59 BASIC BIOLOGICAL SCIENCES↗

Physiological responses in potato plants under continuous irradiation

The physiological responses of four potato (Solanum tuberosum L.) cultivars to continuous irradiation were determined in a controlled environment. Under a constant 18C and a constant photoperiod of 470 micromoles s-1 m-2 of photosynthetic photon flux, 'Denali' and 'Haig' grew well and produced large plant and tuber dry weights when harvested 56 days after transplanting. 'Kennebec' and 'Superior' were severely stunted, producing only 10% of the plant dry matter produced by 'Denali' and 'Haig'. The differences in leaf chlorophyll concentration and stomatal conductance were not consistent between these two groups of cultivars. The leaf net CO2 assimilation rates in 'Kennebec' and 'Superior' were lower, and intercellular CO2 partial pressures were higher than in 'Denali' and 'Haig'. These results indicate that inhibition of net CO2 assimilation in 'Kennebec' and 'Superior' was not due to a limiting amount of chlorophyll or to CO2 in the leaf tissues. Concentrations of starch in leaflets of 'Kennebec' and 'Superior' plants were only 10% of those in 'Denali' and 'Haig' plants, although soluble sugar concentrations were similar in the four cultivars. Therefore, the lower net CO2 assimilation rates in stunted 'Kennebec' and 'Superior' plants were not associated with an excess carbohydrate accumulation in the leaves.

NASA Program CELSS↗

Spectroscopy outperforms leaf trait relationships for predicting photosynthetic capacity across different forest types

Leaf trait relationships are widely used to predict ecosystem function in Terrestrial Biosphere Models (TBMs), in which leaf maximum carboxylation capacity (V c,max ), an important trait for modelling photosynthesis, can be inferred from other easier- to-measure traits. However, whether trait-V c,max relationships are robust across different forest types remains unclear. Here we used measurements of leaf traits, including one morphological trait (leaf mass per area), three biochemical traits (leaf water content, area-based leaf nitrogen content, and leaf chlorophyll content), one physiological trait (V c,max ), as well as leaf reflectance spectra, and explored their relationships within and across three contrasting forest types in China. We found weak and forest type-specific relationships between V c,max and the four morphological and biochemical traits (R 2 ≤ 0.15), indicated by significantly changing slopes and intercepts across forest types. In contrast, reflectance spectroscopy effectively collapsed the differences in the trait-V c,max relationships across three forest biomes into a single robust model for V c,max (R 2 = 0.77), and also accurately estimated the four traits (R 2 = 0.75-0.94). Furthermore, these findings challenge the traditional use of empirical trait-V c,max relationships in TBMs for estimating terrestrial plant photosynthesis, but also highlight spectroscopy as an efficient alternative for characterizing V c,max and multi-trait variability, with critical insights into ecosystem modeling and functional trait ecology.

54 ENVIRONMENTAL SCIENCES↗

Low potassium enhances sodium uptake in red-beet under moderate saline conditions

Due to the discrepancy in metabolic sodium (Na) requirements between plants and animals, cycling of Na between humans and plants is limited and critical to the proper functioning of bio-regenerative life support systems, being considered for long-term human habitats in space (e.g., Martian bases). This study was conducted to determine the effects of limited potassium (K) on growth, Na uptake, photosynthesis, ionic partitioning, and water relations of red-beet (Beta vulgaris L. ssp. vulgaris) under moderate Na-saline conditions. Two cultivars, Klein Bol, and Ruby Queen were grown for 42 days in a growth chamber using a re-circulating nutrient film technique where the supplied K levels were 5.0, 1.25, 0.25, and 0.10 mM in a modified half-strength Hoagland solution salinized with 50 mM NaCl. Reducing K levels from 5.0 to 0.10 mM quadrupled the Na uptake, and lamina Na levels reached -20 g kg-1 dwt. Lamina K levels decreased from -60 g kg-1 dwt at 5.0 mM K to -4.0 g kg-1 dwt at 0.10 mM K. Ruby Queen and Klein Bol responded differently to these changes in Na and K status. Klein Bol showed a linear decline in dry matter production with a decrease in available K, whereas for cv. Ruby Queen, growth was stimulated at 1.25 mM K and relatively insensitive to a further decreases of K down to 0.10 mM. Leaf glycinebetaine levels showed no significant response to the changing K treatments. Leaf relative water content and osmotic potential were significantly higher for both cultivars at low-K treatments. Leaf chlorophyll levels were significantly decreased at low-K treatments, but leaf photosynthetic rates showed no significant difference. No substantial changes were observed in the total cation concentration of plant tissues despite major shifts in the relative Na and K uptake at various K levels. Sodium accounted for 90% of the total cation uptake at the low K levels, and thus Na was likely replacing K in osmotic functions without negatively affecting the plant water status, or growth. Our results also suggest that cv. Ruby Queen can tolerate a much higher Na tissue concentration than cv. Klein Bol before there is any growth reduction. Grant numbers: 12180.

NASA Center KSC↗

Effect of Elevated Atmospheric CO2 and Temperature on Leaf Optical Properties and Chlorophyll Content in Acer saccharum (Marsh.)

Elevated atmospheric CO2 pressure and numerous causes of plant stress often result in decreased leaf chlorophyll contents and thus would be expected to alter leaf optical properties. Hypotheses that elevated carbon dioxide pressure and air temperature would alter leaf optical properties were tested for sugar maple (Acer saccharum Marsh.) in the middle of its fourth growing season under treatment. The saplings had been growing since 1994 in open-top chambers at Oak Ridge, Tennessee under the following treatments: 1) Ambient CO2 pressure and air temperature (control); 2) CO2 pressure approximately 30 Pa above ambient; 3) Air temperatures 3 C above ambient; 4) Elevated CO2 and air temperature. Spectral reflectance, transmittance, and absorptance in the visible spectrum (400-720 nm) did not change significantly (rho = 0.05) in response to any treatment compared with control values. Although reflectance, transmittance, and absorptance at 700 nm correlated strongly with leaf chlorophyll content, chlorophyll content was not altered significantly by the treatments. The lack of treatment effects on pigmentation explained the non-significant change in optical properties in the visible spectrum. Optical properties in the near-infrared (721-850 nm) were similarly unresponsive to treatment with the exception of an increased absorptance in leaves that developed under elevated air temperature alone. This response could not be explained by the data, but might have resulted from effects of air temperature on leaf internal structure. Results indicated no significant potential for detecting leaf optical responses to elevated CO2 or temperature by the remote sensing of reflected radiation in the 400-850 nm spectrum.

Carter, Gregory A.↗

Determination of Chlorophyll Content in Selected Grass Communities of Krkonoše Mts. Tundra Based on Laboratory Spectroscopy and Aerial Hyperspectral Data

The study focuses on the determination of chlorophyll content in four prevailing grasses in the relict arctic-alpine tundra located in the Krkonoše Mountains National Park, Czech Republic. We compared two methods for determination of leaf chlorophyll content (LCC) – spectrophotometric determination in the laboratory, and the LCC assessed by fluorescence portable chlorophyll meter CCM-300. Relationships were established between the LCCs and vegetation indices calculated from leaf spectra acquired with contact probe coupled with an ASD FieldSpec4 Wide-Res spectroradiometer. Canopy chlorophyll contents (CCC) were computed from the LCCs and green leaf area index (LAI), and modelled based on the field spectra measured by the spectroradiometer and the hyperspectral images acquired by Headwall Nano-Hyperspec® mounted on the DJI Matrice 600 Pro drone. The calculations are performed on datasets acquired in June, July and August 2020 together and separately for species and months. In general, the correlations based on June datasets work the best at both levels: median R 2 for all indices was 0.52 for all species together at leaf level and median R 2 = 0.47 at the canopy level (vegetation indices computed from field spectra). Canopy chlorophyll content map was created based on the results of stepwise multiple linear regression. The R 2 was 0.42 when using four wavelengths from the red and red edge spectral region. We attribute the weak model performance to a combination of several factors: leaf structure may bias LCC from laboratory measurements, effects of LAI variability on CCC, and the sampling design, probably not covering the whole phenology equally for all studied species.

L. Cervena↗

How far can sodium substitute for potassium in red beet?

Sodium (Na) movement between plants and humans is one of the more critical aspects of bioregenerative systems of life support, which NASA is studying for the establishment of long-term bases on the Lunar or Martian surface. This study was conducted to determine the extent to which Na can replace potassium (K) in red beet (Beta vulgaris L. ssp vulgaris) without adversely affecting metabolic functions such as water relations, photosynthetic rates, and thus growth. Two cultivars, Ruby Queen and Klein Bol, were grown for 42 days at 1200 micromoles mol-1 CO2 in a growth chamber using a re-circulating nutrient film technique with 0%, 75%, 95%, and 98% Na substitution for K in a modified half-strength Hoagland solution. Total biomass of Ruby Queen was greatest at 95% Na substitution and equal at 0% and 98% Na substitution. For Klein Bol, there was a 75% reduction in total biomass at 98% Na substitution. Nearly 95% of the total plant K was replaced with Na at 98% Na substitution in both cultivars. Potassium concentrations in leaves decreased from 120 g kg-1 dwt in 0% Na substitution to 3.5 g kg-1 dwt at 98% Na substitution. Leaf chlorophyll concentration, photosynthetic rate, and osmotic potential were not affected in either cultivar by Na substitution for K. Leaf glycinebetaine levels were doubled at 75% Na substitution in Klein Bol, but decreased at higher levels of Na substitution. For Ruby Queen, glycinebetaine levels in leaf increased with the first increase of Na levels and were maintained at the higher Na levels. These results indicate that in some cultivars of red beet, 95% of the normal tissue K can be replaced by Na without a reduction in growth.

NASA Discipline Life Support Systems↗

Airborne hyperspectral imaging of nitrogen deficiency on crop traits and yield of maize by machine learning and radiative transfer modeling

Nitrogen is an essential nutrient that directly affects plant photosynthesis, crop yield, and biomass production for bioenergy crops, but excessive application of nitrogen fertilizers can cause environmental degradation. To achieve sustainable nitrogen fertilizer management for precision agriculture, there is an urgent need for nondestructive and high spatial resolution monitoring of crop nitrogen and its allocation to photosynthetic proteins as that changes over time. Here, we used visible to shortwave infrared (400–2400 nm) airborne hyperspectral imaging with high spatial (0.5 m) and spectral (3–5 nm) resolutions to accurately estimate critical crop traits, i.e., nitrogen, chlorophyll, and photosynthetic capacity (CO 2 -saturated photosynthesis rate, V max,27 ), at leaf and canopy scales, and to assess nitrogen deficiency on crop yield. We conducted three airborne campaigns over a maize (Zea mays L.) field during the growing season of 2019. Physically based soil-canopy Radiative Transfer Modeling (RTM) and data-driven approaches i.e. Partial-Least Squares Regression (PLSR) were used to retrieve crop traits from hyperspectral reflectance, with ground truth of leaf nitrogen, chlorophyll, V max,27 , Leaf Area Index (LAI), and harvested grain yield. To improve computational efficiency of RTMs, Random Forest (RF) was used to mimic RTM simulations to generate machine learning surrogate models RTM-RF. The results show that prior knowledge of soil background and leaf angle distribution can significantly reduce the ill-posed RTM retrieval. RTM-RF achieved a high accuracy to predict leaf chlorophyll content (R 2 = 0.73) and LAI (R 2 = 0.75). Meanwhile, PLSR exhibited better accuracy to predict leaf chlorophyll content (R 2 = 0.79), nitrogen concentration (R 2 = 0.83), nitrogen content (R 2 = 0.77), and V max,27 (R 2 = 0.69) but required measured traits for model training. We also found that canopy structure signals can enhance the use of spectral data to predict nitrogen related photosynthetic traits, as combining RTM-RF LAI and PLSR leaf traits well predicted canopy-level traits (leaf traits × LAI) including canopy chlorophyll (R 2 = 0.80), nitrogen (R 2 = 0.85) and V max,27 (R 2 = 0.82). Compared to leaf traits, we further found that canopy-level photosynthetic traits, particularly canopy V max,27 , have higher correlation with maize grain yield. This study highlights the potential for synergistic use of process-based and data-driven approaches of hyperspectral imaging to quantify crop traits that facilitate precision agricultural management to secure food and bioenergy production.

54 ENVIRONMENTAL SCIENCES↗

Global variation in the fraction of leaf nitrogen allocated to photosynthesis

Plants invest a considerable amount of leaf nitrogen in the photosynthetic enzyme ribulose-1,5-bisphosphate carboxylase-oxygenase (RuBisCO), forming a strong coupling of nitrogen and photosynthetic capacity. Variability in the nitrogen-photosynthesis relationship indicates different nitrogen use strategies of plants (i.e., the fraction nitrogen allocated to RuBisCO; fLNR), however, the reason for this remains unclear as widely different nitrogen use strategies are adopted in photosynthesis models. Here, we use a comprehensive database of in situ observations, a remote sensing product of leaf chlorophyll and ancillary climate and soil data, to examine the global distribution in fLNR using a random forest model. We find global fLNR is 18.2 ± 6.2%, with its variation largely driven by negative dependence on leaf mass per area and positive dependence on leaf phosphorus. Some climate and soil factors (i.e., light, atmospheric dryness, soil pH, and sand) have considerable positive influences on fLNR regionally. This study provides insight into the nitrogen-photosynthesis relationship of plants globally and an improved understanding of the global distribution of photosynthetic potential.

54 ENVIRONMENTAL SCIENCES↗

A Passive Method for Detecting Vegetation Stress from Orbit: Chlorophyll Fluorescence Spectra from Fraunhofer Lines

Solar-stimulated chlorophyll fluorescence measured with the Fraunhofer line depth method has correlated well with vegetation stress in previous studies. However, the instruments used in those studies were limited to a single solar absorption line (e.g. 656.3 nm), obviating the red/far-red ratio (R/FR) method. Optics and detector technology have reached the level whereby multiple, very narrow Fraunhofer lines are resolvable. Thirteen such lines span the visible spectrum in the red to far-red region where chlorophyll fluorescence occurs. Fluorescence intensities at the 13 Fraunhofer line wavelengths were used to model emission spectra. The source data were collected for summer and fall bean crops (Phaseolus vulgaris L.) subjected to various levels of nitrogen fertilization. The intensities were adjusted to account for Fraunhofer line depth and atmospheric transmittance. Multiple R/FR fluorescence ratios, calculated from the modeled fluorescence spectra, correlated strongly with leaf chlorophyll concentration and well with applied nitrogen. The ratio yielding the best correlation with chlorophyll utilized red fluorescence at the 694.5 nm Fraunhofer line and farred fluorescence at the 755.6 nm Fraunhofer line. Twenty R/FR ratios, each evaluated for the maximum differential between low and high (optimal) nitrogen treatments, ranked higher in some cases and lower in others, possibly related to the time of year the crops were grown and the stage of growth of the crops. Ratios with 728.9 nm and 738.9 nm in the denominator consistently ranked in the lowest and next lowest quartile, respectively. Ratios of the 656.3 nm Fraunhofer line and the 755.6 nm line consistently ranked highest for the summer crop. Ratios with 755.6 nm in the denominator ranked in the upper quartile for 10 out of 12 measurement dates. Differences in ratio ranking indicate that physiological conditions may be estimated using selected ratios of Fraunhofer lines within the context of R/FR analysis. A passive instrument designed to monitor R/FR chlorophyll fluorescence (i.e. vegetation stress) from orbit could be built today.

Theisen, Arnold F.↗

Comparison of total emitted solar-induced chlorophyll fluorescence (SIF) and top-of-canopy (TOC) SIF in estimating photosynthesis

We report many studies have shown that solar-induced fluorescence (SIF) has a good potential to predict gross primary production (GPP) of vegetation. What we measured by remote sensing or near-surface platforms is top-of-canopy (TOC) SIF (SIF toc ), which is not necessarily equal or proportional to total emitted SIF (SIF tot ) from the entire canopy due to the (re)absorption and scattering effects. However, photosynthesis, the process that plants use to fix carbon from the atmosphere, occurs at the entire vertical canopy. Here, by using the recollision theory, we calculated SIF tot at 760 nm from the measured SIF toc , hyperspectral reflectance (R), canopy interception (i) and leaf albedo (ω l ). Among them, both SIF toc and R can be obtained from concurrent TOC spectral measurements; i and ω l in the near-infrared region can be estimated from the open access datasets with a good accuracy. Our result confirms that the measured SIF toc only accounts for a small fraction of SIF tot : the above-the-canopy sensor can only “see” on average 22.9% of SIF tot at Harvard Forest. SIF tot has the following advantages over SIF toc in estimating GPP: (1) SIF tot improves the diurnal estimate of canopy GPP, especially capable to capture the midday depression of photosynthesis which may cause the large discrepancies between SIF toc and GPP on a diurnal basis, (2) SIF tot produces a stronger correlation with GPP from plants with complex canopy structure or under sky conditions with more diffuse irradiance, and (3) the SIF tot -GPP relationship shows a stronger resilience to environmental stresses. The fluorescence escape ratio (f esc ), the ratio between SIF toc multiplied by π and SIF tot , is mostly determined by the sun-canopy-sensor geometry and leaf inclination distribution. The effect of LAI and the leaf chlorophyll concentration on f esc is marginal at the 760 nm wavelength. Our results suggest that converting SIF toc into SIF tot provides a better tool to understand and estimate GPP.

54 ENVIRONMENTAL SCIENCES↗

Multi-site assessment of the potential of fine resolution red-edge vegetation indices for estimating gross primary production

Gross primary production (GPP) models driven by fine resolution remote sensing data characterize the spatial and temporal heterogeneities in plant photosynthesis, which is largely dependent on biome-specific maximum photosynthetic capacity. The red-edge reflectance, sensitive to leaf chlorophyll content, is a good proxy of maximum photosynthetic capacity. More importantly, studies show that the red-edge reflectance-related chlorophyll content index (CIr) multiplied by the incident photosynthetic active radiation (PAR in ) strongly correlates to GPP estimated at carbon flux towers (GPP flux ). Yet, to the best of our knowledge, there is no systematic study investigating the general relationship between fine spatial resolution CIr and GPP among biomes and the relationship between CIr and maximum photosynthetic capacity in GPP models. To provide an overview on incorporating space-borne CIr into a GPP model, we applied fine resolution Sentinel-2-derived CIr and GPP flux over 57 flux sites representative of 10 biomes. We investigated the relationship between CIr and GPP flux , and the spatio-temporal relationship between CIr and ecosystem maximum photosynthetic capacity indicated by the potential ecosystem light use efficiency (LUE pot ). We also evaluated the relationship between other five vegetation indices (VIs) and GPP flux . Results showed that the CIr multiplied by PARin has a higher agreement (R 2 > 0.5) with GPP than other VIs. A universal relationship exists between the CIr multiplied by PARin and GPP, except for forest biomes. The CIr also strongly (R 2 > 0.5) relates to the LUE pot during the peak of the growing season. The CIr has a low spatial variance (CV = 0.25) among biomes, highlighting that CIr can be a proxy of maximum photosynthetic capacity in GPP models that do not require biome-dependent coefficients. This study provides insight for incorporating CIr into GPP models and better quantifying global terrestrial photosynthesis.

59 BASIC BIOLOGICAL SCIENCES↗

Dissecting the contributions to non-photochemical quenching in a land plant under fluctuating light

Photosynthetic organisms have evolved multiple non-photochemical quenching (NPQ) processes, providing photoprotection by safely dissipating excess excitation energy. These processes involve various molecular players functioning on overlapping timescales from seconds to days, making it challenging to isolate and quantify their individual kinetics. In this study, we perform whole-leaf chlorophyll fluorescence lifetime and xanthophyll concentration measurements on wild-type and various newly characterized NPQ mutants of Nicotiana benthamiana, a vascular land plant. Based on these measurements, we construct a fluorescence lifetime-based quantitative kinetic model that disentangles individual photoprotection components and, when integrated additively, accurately predicts wild-type and mutant NPQ behaviors under various light-dark regimes. Additionally, the model quantifies the per-molecule quenching effectiveness of various xanthophylls and the contributions of six quenching components (qE V , qE A , qE Z , qE L , qZ, and qI) across different genotypes. It also suggests improved overall quenching efficiency at specific VDE:ZEP:PsbS overexpression stoichiometries, aligning with previous studies and supporting translational efforts to optimize photoprotection and enhance crop yields under dynamic light environments.

Lam, Lam [University of California, Berkeley, CA (↗

Competing effects of soil fertility and toxicity on tropical greening

Tropical forests are expected to green up with increasing atmospheric CO 2 concentrations, but primary productivity may be limited by soil nutrient availability. However, rarely have canopy-scale measurements been assessed against soil measurements in the tropics. Here, we sought to assess remotely sensed canopy greenness against steep soil nutrient gradients across 50 1-ha mature forest plots in Panama. Contrary to expectations, increases in in situ extractable soil phosphorus (P) and base cations (K, Mg) corresponded to declines in remotely sensed mean annual canopy greenness (r 2 = 0.77– 0.85; p < 0.1), controlling for precipitation. The reason for this inverse relationship appears to be that litterfall also increased with increasing soil P and cation availability (r 2 = 0.88–0.98; p < 0.1), resulting in a decline in greenness with increasing annual litterfall (r 2 = 0.94; p < 0.1). As such, greater soil nutrient availability corresponded to greater leaf turnover, resulting in decreased greenness. However, these decreases in greenness with increasing soil P and cations were countered by increases in greenness with increasing soil nitrogen (N) (r 2 = 0.14; p < 0.1), which had no significant relationship with litterfall, likely reflecting a direct effect of soil N on leaf chlorophyll content, but not on litterfall rates. In addition, greenness increased with extractable soil aluminum (Al) (r 2 = 0.97; p < 0.1), but Al had no significant relationship with litterfall, suggesting a physiological adaptation of plants to high levels of toxic metals. Thus, spatial gradients in canopy greenness are not necessarily positive indicators of soil nutrient scarcity. Using a novel remote sensing index of canopy greenness limitation, we assessed how observed greenness compares with potential greenness. We found a strong relationship with soil N only (r 2 = 0.65; p < 0.1), suggesting that tropical canopy greenness in Panama is predominantly limited by soil N, even if plant productivity (e.g., litterfall) responds to rock-derived nutrients. Moreover, greenness limitation was also significantly correlated with fine root biomass and soil carbon stocks (r 2 = 0.62–0.71; p < 0.1), suggesting a feedback from soil N to canopy greenness to soil carbon storage. Altogether, these data point to the potential utility of a remote sensing product for assessing belowground properties in tropical ecosystems.

54 ENVIRONMENTAL SCIENCES↗

KARRIKIN INSENSITIVE2 regulates leaf development, root system architecture and arbuscular‐mycorrhizal symbiosis in Brachypodium distachyon

SUMMARY KARRIKIN INSENSITIVE2 (KAI2) is an α/β‐hydrolase required for plant responses to karrikins, which are abiotic butenolides that can influence seed germination and seedling growth. Although represented by four angiosperm species, loss‐of‐function kai2 mutants are phenotypically inconsistent and incompletely characterised, resulting in uncertainties about the core functions of KAI2 in plant development. Here we characterised the developmental functions of KAI2 in the grass Brachypodium distachyon using molecular, physiological and biochemical approaches. Bdkai2 mutants exhibit increased internode elongation and reduced leaf chlorophyll levels, but only a modest increase in water loss from detached leaves. Bdkai2 shows increased numbers of lateral roots and reduced root hair growth, and fails to support normal root colonisation by arbuscular‐mycorrhizal (AM) fungi. The karrikins KAR 1 and KAR 2 , and the strigolactone (SL) analogue rac ‐GR24, each elicit overlapping but distinct changes to the shoot transcriptome via BdKAI2. Finally, we show that BdKAI2 exhibits a clear ligand preference for desmethyl butenolides and weak responses to methyl‐substituted SL analogues such as GR24. Our findings suggest that KAI2 has multiple roles in shoot development, root system development and transcriptional regulation in grasses. Although KAI2‐dependent AM symbiosis is likely conserved within monocots, the magnitude of the effect of KAI2 on water relations may vary across angiosperms.

Meng, Yongjie↗

Sustainability Trait Modeling of Field-Grown Switchgrass (Panicum virgatum) Using UAV-Based Imagery

Unmanned aerial vehicles (UAVs) provide an intermediate scale of spatial and spectral data collection that yields increased accuracy and consistency in data collection for morphological and physiological traits than satellites and expanded flexibility and high-throughput compared to ground-based data collection. In this project, we used UAV-based multispectral imagery collected from MicaSense RedEdge-M on a DJI Matrice 600 Pro for automated phenotyping of field-grown switchgrass (Panicum virgatum), a leading bioenergy feedstock. The raw images were processed with Pix4D Mapper to create the reflectance data, and vegetation indices were calculated from a UAV-based multispectral camera. Statistical models were developed for rust disease caused by Puccinia novopanici, leaf chlorophyll, nitrogen, and lignin contents. For the first time, UAV remote sensing technology was used to explore the potential for multiple traits associated with sustainable production of switchgrass. One statistical model was developed for each individual trait based on the statistical correlation between vegetation indices and the corresponding trait.

CBI↗